✦ Luna Orbit — AI & Machine Learning

Data Scientist

at Motorola Solutions

📍 Richardson, TX (TX145) Hybrid Posted April 14, 2026
Type Full-Time
Experience mid
Exp. Years 3 years experience (with Bachelor's degree) or 1 year experience (with Masters degree)
Education Bachelors degree + 3 years experience or Masters degree + 1 year experience
Category AI & Machine Learning

This role develops statistical and machine learning solutions to drive data-driven decision-making and predictive insights. It also designs AI-powered chatbots using large language models (LLMs) with Retrieval-Augmented Generation (RAG) and builds the data pipelines needed to power analytics and real-time responses.

  • Develop and implement statistical models, machine learning algorithms, and predictive analytics
  • Design and build data pipelines for ingestion, transformation, and storage
  • Create dashboards, reports, and visualizations for technical and non-technical audiences
  • Design and implement AI-powered chatbots using large language models (LLMs), Retrieval-Augmented Generation (RAG) architecture, and vectorization techniques
  • Perform exploratory data analysis (EDA) and hypothesis testing to support business intelligence

You will collect, preprocess, and analyze structured and unstructured data using exploratory data analysis (EDA) and hypothesis testing. The job emphasizes building data pipelines and implementing LLM-based chatbots with RAG architecture and vectorization to enable natural language querying over enterprise data.

The ideal candidate is a mid-level Data Scientist experienced with predictive analytics, machine learning algorithms, and building data pipelines for structured and unstructured data. They have hands-on LLM experience, including Retrieval-Augmented Generation (RAG) architectures and vectorization, and can deliver analytics outputs via dashboards and visualizations for both technical and non-technical stakeholders.

Collectcleanand preprocess large volumes of structured and unstructured dataDevelop and implement statistical modelsmachine learning algorithmsand predictive analyticsDesign and build data pipelines and automated processes for data ingestiontransformationand storageCreate dashboardsreportsand visualizationsDesign and implement AI-powered chatbots leveraging large language models (LLMs)Retrieval-Augmented Generation (RAG) architectureand vectorization techniquesPerform exploratory data analysis (EDA) and hypothesis testing
large language models (LLMs)Retrieval-Augmented Generation (RAG) architecture
collectcleanand preprocess large volumes of structured and unstructured datastatistical modelsmachine learning algorithmspredictive analyticsdata pipelinesdata ingestiondata transformationdata storagecross-functional teamsdashboardsreportsvisualizationsAI-powered chatbotslarge language models (LLMs)Retrieval-Augmented Generation (RAG) architecturevectorization techniquesnatural languagereal-timecontext-aware responsesexploratory data analysis (EDA)hypothesis testing
collectcleanand preprocess large volumes of structured and unstructured datadata-driven decision-makingstatistical modelsmachine learning algorithmspredictive analyticsdesign and build data pipelinesautomated processes for data ingestiondata transformationdata storageexploratory data analysis (EDA)hypothesis testingdashboardsreportsvisualizationsAI-powered chatbotslarge language models (LLMs)Retrieval-Augmented Generation (RAG) architecturevectorization techniquesnatural languagereal-timecontext-aware responsesenterprise data queryingdata sources from structured and unstructured enterprise datacross-functional collaboration for data requirements
collaborationcross-functional teamworkcommunication with technical and non-technical audiencesstakeholder managementanalytical thinkingproblem-solving
Industry SaaS
Job Function Build predictive analytics and LLM-powered RAG chatbot solutions backed by robust data pipelines
Role Subtype ML Engineer
Tech Domains AI & Machine Learning, SaaS, Data Engineering
Data Scientistcollectcleanand preprocess large volumes of structured and unstructured datastatistical modelsmachine learning algorithmspredictive analyticsdata pipelinesdata ingestiondata transformationdata storagecross-functional teamsdashboardsreportsvisualizationsAI-powered chatbotslarge language models (LLMs)Retrieval-Augmented Generation (RAG) architecturevectorization techniquesnatural languagereal-timecontext-aware responsesexploratory data analysis (EDA)hypothesis testingdata-driven decision-makingtelecommuting permitted up to 2 days per week

Must meet education/experience requirement: Bachelor's degree + 3 years experience OR Masters degree + 1 year experience, Must have experience implementing machine learning algorithms and predictive analytics, Must have LLM chatbot experience using Retrieval-Augmented Generation (RAG) architecture and vectorization techniques

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